| Literature DB >> 27652111 |
Ying Liang1, Wenhui Yang2, Yanhui Zhu2, Yulin Yuan2.
Abstract
Growing evidence from recent studies has revealed that microRNA-203 (miR-203) might be an attractive prognostic biomarker for cancer. But controversy still remains. The aim of this meta-analysis was to summarize available evidences and clarify the preliminary predictive value of miR-203 for prognosis in cancer patients. Eligible studies were identified through multiple research strategies in PubMed, EMBASE and Web of Science up to October 2015. Key statistics such as pooled hazard ratios (HR) with 95 % confidence intervals (CIs) were utilized to calculate patient survival. 13 eligible studies with 1600 patients were ultimately enrolled in this meta-analysis. Our results failed to show a significant relation between upregulated miR-203 expression and a favorable overall survival (OS) (HR 1.00, 95 % CI 0.65-1.36) in a random effect model. However, in subgroup analysis, we found that high expression of miR-203 was significantly associated with poor OS in Caucasian patients (HR 1.31, 95 % CI 1.06-1.55). In contrast, for Asian patients, over-expression of miR-203 was an independent prognostic factor for better and OS (HR 0.59, 95 % CI 0.22-0.96). It also suggested that cancer types and miRNA assay method were significant associated with prognosis. The over-expression of miR-203 was effectively predictive of worse prognosis in breast cancer (HR 6.35, 95 % CI 1.34-11.36), pancreatic cancer (HR 1.19, 95 % CI 1.08-1.30), ependymoma (HR 1.35, 95 % CI 1.10-1.61), but for glioma patients, elevated miR-203 is a potential biomarker for predicting better progression of cancer (HR 0.26, 95 % CI -0.02 to 0.54). Besides, for direct miRNA profiling studies, over-expression of miR-203 was an independent prognostic factor for worse OS (HR 6.35, 95 % CI 1.34-11.36). This meta-analysis indicated that ethnicity, tumor type and miRNA assay method mainly contributed to heterogeneity. Considering the insufficient evidence, further relevant studies are warranted.Entities:
Keywords: Cancer; MicroRNA-203; Overall survival; Prognosis
Year: 2016 PMID: 27652111 PMCID: PMC5020041 DOI: 10.1186/s40064-016-3225-y
Source DB: PubMed Journal: Springerplus ISSN: 2193-1801
Fig. 1Flow diagram of the study selection process
Characteristics of studies included in the meta-analysis
| First author | Years | Country | Gender | Median age (years) | Disease | Number | Stage I–II/III–IV | miR-203 assay | Source of HR | Maximum months of follow-up |
|---|---|---|---|---|---|---|---|---|---|---|
| Chen | 2012 | China | 56/10 | 56 (40–73) | Hepatocellular | 66 | 59/7 | qRT-PCR | Reported | 100 |
| Liu | 2015 | China | 75/20 | 52 (29–82) | Hepatocellular | 95 | 22/73 | qRT-PCR | Survival curves | 68 |
| He | 2013 | China | 70/42 | 44 (6–86) | Glioma | 112 | 38/74 | qRT-PCR | Survival curves | 161 |
| Bovell | 2013 | USA | 170/175 | <65 169; ≥ 65 176 | Colorectal | 345 | 184/161 | qRT-PCR | Reported | 348 |
| Schetter | 2008 | USA | 66/18 | 64.6 (32–87) | Colorectal | 84 | 37/46 | qRT-PCR | Reported | 141.9 |
| Wang | 2013 | China | NR | 50.2 (30–70) | Ovarian | 156 | 48/108 | qRT-PCR | Survival curves | 88 |
| Madhavan | 2012 | Germany | NR | 61 (30–92) | Breast | 133 | 104/26 | Profiling | Survival curves | 10.8 |
| Imaoka | 2015 | Japan | 91/39 | 68 | Gastric | 130 | 69/61 | qRT-PCR | Reported | 78 |
| Ikenaga | 2010 | Japan | 71/42 | 66 (36–86) | Pancreatic | 113 | 109/4 | qRT-PCR | Survival curves | 98 |
| Greither | 2010 | Germany | NR | NR | Pancreatic | 50 | NR | qRT-PCR | Survival curves | NR |
| Nicolai | 2012 | Denmark | 111/114 | 64 (31–85) | Pancreatic | 225 | 35/180 | qRT-PCR | Reported | 196 |
| Costa | 2011 | USA | 13/21 | NR | Ependymoma | 34 | 22/12 | qRT-PCR | Reported | 160.8 |
| Mathé a | 2009 | USA | 12/12 | <62 11; ≥ 62 13 | Esophagus | 24 | 21/3 | qRT-PCR | Survival curves | NR |
| Mathé b | 2009 | Japan | 30/3 | <62 14; ≥ 62 19 | Esophagus | 33 | 19/14 | qRT-PCR | Reported | NR |
NR not reported, qRT-PCR quantitative reverse transcription PCR
Fig. 2Forest plots of the analyses about miR-203 and overall survival with tumors
Fig. 3Forest plots derived from the analyses of Caucasians and Asians studies
Fig. 4Forest plots derived from the analyses of various cancers
Fig. 5Forest plots derived from the analyses of different assay methods
Fig. 6Funnel plots provided graphic estimate of bias for overall studies